Dialogue with Hedra Founder Michael Lingelbach: How Generative Video Leverages Memes to Create the Next Trend

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2025-08-18 22:22:19

Collection

"Perhaps AI characters and virtual influencers are the next trend in the video field."

Original Title: Why AI Characters \& Virtual Influencers Are the Next Frontier in Video ft Hedra's Michael Lingelbach

Hosts: Justine Moore, Matt Bornstein, a16z

Guest: Michael Lingelbach

Edited \& Compiled by: Janna, ChainCatcher

Editor's Note

Michael Lingelbach is the founder and CEO of Hedra. He was a PhD student in Computer Science at Stanford University and a stage actor, combining his passion for technology and performance to lead Hedra in developing industry-leading generative audio and video models. Hedra is a company focused on full-body embodiment and dialogue-driven video generation, with technology that supports a wide range of applications from virtual influencers to educational content, significantly lowering the barriers to content creation. This article is adapted from the a16z podcast, focusing on how AI technology is transitioning from viral meme content to enterprise-level applications, showcasing the innovative potential of generative audio and video technology.

The following is the dialogue content, compiled and edited by ChainCatcher (with some omissions).

TL\&DR

AI is seamlessly bridging consumer and enterprise scenarios, as evidenced by this technology generating baby ads promoting enterprise software, highlighting companies' enthusiasm for embracing new technologies.
Viral meme content has become a powerful tool for startups, such as the "baby podcast" rapidly boosting brand awareness, showcasing clever market strategies.
Full-body expression and dialogue-driven video generation technology fill creative gaps, significantly reducing the time and cost of content production.
Virtual influencers like John Lawa shape unique digital characters through the "Moses Podcast," giving content distinct personality and appeal.
Content creators like "mom bloggers" leverage technology to quickly produce videos, easily maintaining brand engagement and audience connection.
Real-time interactive video models open up two-way dialogue with virtual characters, bringing immersive experiences to education and entertainment.
Character-centric video generation technology emphasizes personal expression and multi-agent control, meeting the demands of dynamic content creation.
A platform strategy that integrates dialogue, actions, and rendering creates a seamless generative media experience, catering to the demand for high-quality content.
Interactive avatar models support dynamic adjustments of video emotions and elements, signaling the next wave of innovation in content creation.

(1) The Fusion of AI from Meme to Enterprise Application

Justine: We find the intersection of AI in consumer and enterprise scenarios very interesting. A few days ago, I saw an ad text generated by Hedra on Forbes, featuring a talking baby promoting enterprise software. This indicates that we are in a new era where companies are rapidly embracing AI technology, showing great enthusiasm.

Michael: As a startup, our responsibility is to draw inspiration from consumer user signals and transform them into next-generation content production tools that enterprise users can rely on. In recent months, some viral content generated by Hedra has garnered widespread attention, from early anime-style characters to the "baby podcast," and even this week's trending topics—I’m not quite sure what they are. Memes are a very effective marketing strategy that quickly captures user minds by reaching a large audience. This strategy is becoming increasingly common among startups. For example, another company invested by a16z, Cluey, gained significant brand recognition through viral dissemination on Twitter. The essence of memes is that technology provides a vehicle for people to unleash creativity quickly, and short video content has dominated cultural consciousness. Hedra's generative video technology allows users to turn any idea into content in seconds.

(2) Why Creators and Influencers Choose Hedra

Justine: Can you explain why people use Hedra to create memes, how they use it, and how this relates to your target market?

Michael: Hedra is the first company to deploy full-body expression and dialogue-driven generative video models at scale. We support users in creating millions of pieces of content, and our rapid popularity stems from filling a critical gap in the content creation tech stack. Previously, creating generative podcasts, animated character dialogue scenes, or singing videos was very challenging—either too costly, lacking flexibility, or too time-consuming. Our model is fast and cost-effective, which has spurred the rise of virtual influencers.

Justine: Recently, CNBC published an article about Hedra-driven virtual influencers. Can you give a few specific examples of how influencers are using Hedra?

Michael: For instance, the famous actor John Lawa (who played Taco in "The League") has created a series of content ranging from the "Moses Podcast" to the "Baby Podcast" using Hedra, and these characters now have unique identities. Another example is Neural Viz, which built a character-centric "metaverse" based on Hedra. Generative performance differs from simple media models; it requires injecting personality, consistency, and control into the model, which is particularly important for video performance. Thus, we see the unique personalities of these virtual characters becoming popular, even though they are not real people.

(3) Virtual Influencers and Digital Avatars

Matt: I’ve seen many Hedra videos on Instagram Reels, featuring both newly created characters like the aliens in the Neural Viz series—previously only achievable by Hollywood blockbusters—and real people using these tools to expand their digital presence. Many influencers or content creators don’t want to spend time getting ready, adjusting lighting, or applying makeup every time. Hedra allows people like "mom bloggers" to quickly generate videos to convey messages without spending a lot of time preparing. For example, they can directly generate content talking to the camera using Hedra.

Michael: That’s an important observation. Maintaining a personal brand is crucial for content creators, but staying online 24/7 is very challenging. If a creator pauses updates for a week, they may lose followers. Hedra's automation technology significantly lowers the barriers to creation. Users can generate scripts using tools like Deep Research and then create audio and video content through Hedra, automatically publishing it to their channels. We see an increasing number of workflows around autonomous digital identities, serving not only real people but also entirely fictional characters.

(4) The Potential and Challenges of Interactive Video

Justine: Many historical videos are trending on Reels now. In the past, we gained knowledge through reading history books, but that can be a bit dull. If history could be narrated through characters and showcased in generative video scenes, the experience would be much more engaging.

Michael: Although we don’t directly target the education sector, many educational companies are developing applications based on our API. The engagement of video interactivity is far higher than that of text. We recently launched a real-time interactive video model, the first product to achieve low-latency audio and video experiences. From language learning to personal development applications, when the cost of technology is low enough, it will fundamentally change how users interact with large language models (LLMs). One of my favorite projects is "Chat with Your Favorite Book or Movie Character." For example, you could ask, "Why did you walk into that dark room knowing there was a killer?" This interactive experience is richer than traditional audiobooks because users can ask questions and revisit content, making the experience more vivid.

Justine: The search space for video models is vast. Generating a single frame image is already complex, but generating 120 frames of continuous video is even more challenging. Hedra focuses on a unique and meaningful problem, setting it apart from other video models. Please describe the definition of this problem and your source of inspiration.

Michael: That’s a great question. We see specialization emerging in the foundational model layer, just as Claude has become the benchmark for programming models, OpenAI provides a general assistant, and Gemini serves enterprise scenarios due to cost-effectiveness and speed. Hedra has a similar positioning in the video model space. Our foundational model performs exceptionally well, especially the next-generation model, providing great flexibility for content creation. But we are more focused on how to make content "come alive," encouraging users to interact with it and feel a consistent personality and appeal. The core lies in how to combine the intelligence of characters in videos with the rendering experience. My vision is for users to communicate bidirectionally with characters in videos, where characters have programmable unique personalities. This requires vertical integration, not only optimizing the core model but also rethinking the future experience of user interaction.

(5) Character-Centric Video Models and Subject Control

Michael: I come from a theatrical background; although I’m not a professional actor, I am passionate about character performance. Video is at the core of our daily interactions, whether it’s advertising, online courses, or Hedra-driven faceless channels, the sense of connection is crucial. By lowering the barriers to creation and speeding up the process, we enable ordinary users to easily generate content. In the future, the boundaries between model intelligence and rendering will gradually blur, and users will converse with systems that understand their intentions. We view characters as the core unit of control, not just video. This requires collecting user feedback to optimize the realism and expressiveness of characters while providing control levers for multiple agents.

Matt: I’ve spent a lot of time creating characters for different videos, and the strength of Hedra lies in its integrated character creation tools. You can create or upload character images, save them for later use, and even change contexts or clone voices. Many of my YouTube video and tutorial openings use a cloned version of my voice from Hedra. This integrated experience is particularly valuable in the fragmented generative media market.

(6) Building an Integrated Generative Media Platform

Justine: Many companies like Black Forest Labs have made technological breakthroughs, but they still need partners like Hedra to deliver experiences to consumers and enterprise users. How did you decide to build an integrated platform rather than focusing on a single technology?

Michael: It’s about focus and user needs. When I founded Hedra, I found it very difficult to integrate dialogue into media. In the past, users creating short videos needed to overlay lip-syncing, lacking a sense of wholeness. Our technological inspiration was to unify signals like breathing and gestures with dialogue to create a more natural video model. From a market perspective, we observed differences in users' willingness to pay for different applications. Some popular applications may have low willingness to pay, but certain niches (like content creators) have a strong demand for high-quality experiences. We choose to integrate the best technologies, whether from Hedra or partners like 11 Labs, to ensure users receive the best experience.

Matt: In the future, will AI characters generate text, scripts, voice, and visuals from a single model?

Michael: I believe the industry is moving towards a multimodal input-output paradigm. The challenge with a single model lies in control. Users need to finely adjust details like voice, tone, or rhythm. Decoupling inputs can provide more control, but the future may trend towards fully multimodal models, where users can adjust the fit of each modality through guiding signals.

(7) The Future of Interactive Video

Justine: I’m impressed by Hedra's ability to generate long videos. You can upload a few minutes of audio and generate character dialogue videos, adjusting appearance and voice separately to avoid wasting resources on one-time generation. This level of control makes me excited about the future of interactive video.

Michael: I’m excited about the interactive avatar model we just launched. In the future, users will be able to shape video elements like on a fluid canvas, for example, pausing a video and asking a character to be sadder in a certain line. This kind of two-way communication will bring the next generation of experiences, and it will be realized soon.

Matt: Is it possible to have real AI actors? Users interact in real-time with created characters and give instructions.

Michael: Absolutely possible. But currently, the limitation is not in video models but in the authenticity of personality in large language models. Existing AI companions (like Character AI) still bear obvious model traces. To achieve truly interactive digital characters, more research is needed on configurable personalities.

(8) Hedra's Audio Generation and AI-Native Applications

Justine: Hedra's videos are stunning, but the audio sometimes falls short. 11 Labs' latest model has improved audio quality, but the content's appeal still needs enhancement.

Michael: Audio generation is an underexplored area. Currently, generative speech is mostly used for narration or voiceovers, but generating natural dialogue in noisy environments like a café remains challenging. We need audio models that can control background noise and support multi-turn conversations to enhance the naturalness of video creation. Video AI is still in its early stages. Just like early CGI effects seemed realistic at the time but now look cartoonish, our first-generation models amazed me, but they now seem rough. Achieving highly controllable, cost-effective, and real-time performance models still requires effort.

Matt: Would users prefer to interact with real humans, quasi-human characters, or cartoon characters?

Michael: We’ve generated many furry balls and cat characters. Hedra's unified model can handle various characters, whether they are rocks or robots, allowing users to experiment freely and create unprecedented content. We build a unified model, rather than traditional video with lip-syncing, to avoid limiting users by technology. Users can try "talking rocks" or "podcasts with robots and humans," and the model can automatically handle dialogue and personality. This flexibility sparks revolutionary consumer scenarios.

Justine: The cross-application of AI is exciting. Consumers create content like the "baby podcast," inspiring enterprise applications. I was amazed to see the baby ad generated by Hedra promoting enterprise software in Forbes. This shows that companies are rapidly embracing AI, and we need to translate consumer signals into enterprise-level solutions.

Michael: Enterprises are our fastest-growing sector. Generative AI has shortened content creation from weeks to real-time. For example, automated news anchors are changing the way information is disseminated. In the past, local news disappeared due to high costs, but now one person can operate a news channel. This "medium-scale personalization" meets the needs of specific audiences, such as targeted ads for local cuisine or theme parks, proving more effective than overly personalized Google models.

(9) The Founder’s Journey: Challenges, Passion, and Collaborative Innovation

Justine: As a founder, what has your experience been like? What challenges and rewards have you encountered?

Michael: In San Francisco, the life of a founder is often romanticized, like a journey of building groundbreaking technology. I come from a small town in Florida and never imagined I would take this path. But 99% of being a founder is very tough. You have to keep pushing; the problems never decrease—from invisible development to facing a flood of support emails. Physically, it’s exhausting, but the inner satisfaction is unparalleled. I love my users and my team, and I can’t imagine doing anything else. It’s a kind of "second-order fun"—like climbing a snowy mountain, injuring your hands and feet, but still wanting to come back after reaching the top. I go into the office at 7:30 AM and leave at 10 PM, sometimes still discussing features at 2 AM. It requires sacrificing the boundaries between work and life, but my passion keeps me going.

Matt: Why do you still code personally? Is it to express creativity or to communicate with the team?

Michael: Both. Prototyping helps me quickly validate ideas and clearly communicate expectations. Clear communication is crucial as a leader. I discuss edge cases with designers to ensure the system is scalable. Coding keeps me connected with the team, understanding their challenges while quickly exploring product directions.

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